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                <th scope="col"> </th>
                <th scope="col">(1)</th>
                <th scope="col">(2)</th>
                <th scope="col">(3)</th>
                <th scope="col">(4)</th>
                <th scope="col">(5)</th>
                <th scope="col">(6)</th>
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        <tfoot><tr><td colspan='7'></td></tr>
<tr><td colspan='7'>The outcome variable is XX. Estimates are based on XX. Columns differ with respect to XX. All estimations include the following set of control variables: age, binary for being married, number of children in household, binary for no educational degree, personal income, years of work experience, satisfaction with household income. Robust standard errors in parenthesis. * p &lt; 0.05, ** p &lt; 0.01, *** p &lt; 0.001.</td></tr></tfoot>
        <tbody>
                <tr>
                  <td>ATT       </td>
                  <td>0.154***     </td>
                  <td>−0.009      </td>
                  <td>0.122***     </td>
                  <td>0.049       </td>
                  <td>0.178***       </td>
                  <td>0.029         </td>
                </tr>
                <tr>
                  <td>          </td>
                  <td>(0.034)      </td>
                  <td>(0.047)     </td>
                  <td>(0.029)      </td>
                  <td>(0.075)     </td>
                  <td>(0.040)        </td>
                  <td>(0.037)       </td>
                </tr>
                <tr>
                  <td>intercept </td>
                  <td>0.252***     </td>
                  <td>0.260***    </td>
                  <td>0.249***     </td>
                  <td>0.306***    </td>
                  <td>0.234***       </td>
                  <td>0.282***      </td>
                </tr>
                <tr>
                  <td>          </td>
                  <td>(0.025)      </td>
                  <td>(0.029)     </td>
                  <td>(0.021)      </td>
                  <td>(0.045)     </td>
                  <td>(0.029)        </td>
                  <td>(0.025)       </td>
                </tr>
                <tr>
                  <td>N         </td>
                  <td>1715         </td>
                  <td>718         </td>
                  <td>2164         </td>
                  <td>269         </td>
                  <td>1182           </td>
                  <td>1245          </td>
                </tr>
                <tr>
                  <td>adj. R2   </td>
                  <td>0.01         </td>
                  <td>0.01        </td>
                  <td>0.01         </td>
                  <td>−0.01       </td>
                  <td>0.01           </td>
                  <td>0.01          </td>
                </tr>
                <tr>
                  <td>BIC       </td>
                  <td>2364         </td>
                  <td>988         </td>
                  <td>2981         </td>
                  <td>367         </td>
                  <td>1614           </td>
                  <td>1734          </td>
                </tr>
                <tr>
                  <td>Log.Lik.  </td>
                  <td>−1163        </td>
                  <td>−477        </td>
                  <td>−1472        </td>
                  <td>−169        </td>
                  <td>−789           </td>
                  <td>−849          </td>
                </tr>
                <tr>
                  <td>p-value   </td>
                  <td>0.4547       </td>
                  <td>0.1092      </td>
                  <td>0.8466       </td>
                  <td>0.5769      </td>
                  <td>0.2962         </td>
                  <td>0.191         </td>
                </tr>
                <tr>
                  <td>sub-sample</td>
                  <td>turnout09_yes</td>
                  <td>turnout09_no</td>
                  <td>turnout13_yes</td>
                  <td>turnout13_no</td>
                  <td>politmember_yes</td>
                  <td>politmember_no</td>
                </tr>
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